[R] Help to conduct a random factor analysis with binomial response

[Prof Brian Ripley]

On Wed, 21 Nov 2001, MUGGEO VITO wrote:

> Estimation of GLMM is also implemented in statmod library (reglm() function,
> it should be) by Smith for S+ (unfortunaly I don' t remember the web page)
> that uses the method decribed in Schall (1991).
> This method is substantially a PQL, isn't it or am I wrong?

It is, but the code doesn't run in R without substantial change.  It is
one of the

> > There are some alternatives for S code for PQL about, too, although
> > those I have seen are none too flexible.

I mentioned: it is restricted to additive (unnested) random intercepts.

> Dear Prof. Ripley, were can I find your wrapper around lme that fits GLMMs
> by PQL? maybe can you send me it? Thank you

As I said below.  It is beta, and not released yet, but you can request a
beta version, privately.

> vito
>
>
> ----- Original Message -----
> From: "Prof Brian Ripley" <ripley at stats.ox.ac.uk>
> To: "Douglas Bates" <bates at stat.wisc.edu>
> Cc: "Leif Egil Loe" <l.e.loe at bio.uio.no>; <r-help at stat.math.ethz.ch>;
> <atle.mysterud at bio.uio.no>
> Sent: Tuesday, November 20, 2001 6:58 PM
> Subject: Re: [R] Help to conduct a random factor analysis with binomial
> response
>
>
> > On 20 Nov 2001, Douglas Bates wrote:
> >
> > > Leif Egil Loe <l.e.loe at bio.uio.no> writes:
> > >
> > > > I am a ph.d. student in biology working on red deer in Norway, who
> > > > would like to conduct an analysis with random factor where the
> > > > response is binomially distributed. This cannot be conducted in
> > > > S-plus, and I was told by others that it may be possible in
> > > > R. However, I soon got into trouble which I hope you can help me to
> > > > solve.
> > >
> > > This type of model is a generalized linear mixed model.
> > >
> > > I think you would have to use the GLMMGibbs package in R to analyze
> > > it.  You can't fit this type of model with the nlme package in R or in
> > > S-PLUS.
> >
> > Since there was just a single additive random factor, another alternative
> > is another glmm() in one of Jim Lindsey's packages (gnlr, I think).
> >
> > I had a student exploring some of these over the summer, and there were
> > lots of problem getting GLMMGibbs' glmm to keep running with binary
> > responses (it got internal errors), and a couple of times Lindsey's glmm
> > gave (practically) different answers to all other methods.
> >
> > There will soon be some alternatives.  I have a wrapper around lme that
> > fits GLMMs by PQL, and that is working in R and S-PLUS. It will make the
> > MASS library soon, and I can make beta versions available.  (For S-PLUS
> > Jose' Pinheiro has at alpha/beta a more sophisticated wrapper called GLME,
> > but that depends on the very latest S-PLUS version of NLME).  James
> > McBroom and I have at alpha stage an adaptively tilted numerical
> > quadrature method that seems to do ML fitting fast and accurately thus
> > far.
> >
> > There are some alternatives for S code for PQL about, too, although
> > those I have seen are none too flexible.
> >
> > We (James and I) would be happy to try out what we have on the deer data
> > for you.
> >
> > --
> > Brian D. Ripley,                  ripley at stats.ox.ac.uk
> > Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
> > University of Oxford,             Tel:  +44 1865 272861 (self)
> > 1 South Parks Road,                     +44 1865 272860 (secr)
> > Oxford OX1 3TG, UK                Fax:  +44 1865 272595
> >
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-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272860 (secr)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

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